Research projects generate large, complex datasets that need to be discoverable, shareable, and reusable over time. We work with research organisations to design and implement data management platforms that meet FAIR (Findable, Accessible, Interoperable, Reusable) data principles and enable collaboration across disciplines.
Our expertise covers metadata modelling, ontology design, catalogue services, and integration of heterogeneous datasets. We advise on data strategies and governance as well as delivering sustainable, cloud-based services for ongoing data publication.
We have worked with the UK Centre for Ecology & Hydrology, The National Archives and AstraZeneca UK on platforms that enable research data to be stored, found, accessed, and reused long after individual projects have ended. By embedding interoperability and openness, we ensure research data continues to create value for science and society.
Common challenges we solve:
- Data discoverability: research outputs are often buried in PDFs or project silos.
- Reproducibility challenges: lack of consistent standards and metadata limits reuse.
- FAIR compliance: researchers need practical ways to implement FAIR.
- Data lifecycle management projects end but data must be preserved for decades.
- Heterogeneous datasets: combining data across disciplines, scales, and file types.
See Our Projects pages for examples of our work
UK CEH
AstraZeneca UK
Working with Epimorphics
If your organisation is grappling with research data fragmentation, poor discovery, or AI‑readiness of datasets – we can help you design a sustainable, connected research data ecosystem.
